gobbler AGENTS.md

Repository instructions for developing Gobbler, covering installation, tests, formatting, type checks, documentation, and project structure.

In plain words
What is it for?
They are for setting up Gobbler, running unit or integration tests, checking types and style, building documentation, and preparing changes for review.
Why use it?
They give coding agents the project’s required commands and development conventions in one place.

Instructions file for CodexOpenCode

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add instructions/enablement-engineering/gobbler/agents-md
Clone the repo
git clone --depth 1 https://github.com/Enablement-Engineering/gobbler

Made for: Codex, OpenCode.

Per session 1,122 This file is loaded in full into every session.
When invoked 1,122 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.01122 $0.01122
Opus 5 $0.00561 $0.00561
Sonnet 5 $0.00224 $0.00224
Haiku 4.5 $0.00112 $0.00112

Measured 2d ago against content hash 62c7b22b0f49, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

gobbler AGENTS.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

AGENTS.md · 162 lines

How it starts

The opening of the file, as written. The whole thing — 162 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md - Gobbler Development Guidelines

Guidelines for AI coding agents. See CONTRIBUTING.md for full details.

Quick Reference

# Install
make dev                    # Development install with all extras

# Tests
make test                   # Unit tests
make test-unit              # Unit tests only
make test-integration       # Integration tests
make test-all               # Unit + integration + end-to-end tests
uv run pytest tests/unit/test_youtube_converter.py -v                        # Single file
uv run pytest tests/unit/test_youtube_converter.py::TestVideoIdExtraction -v # Single class
uv run pytest tests/unit/test_youtube_converter.py::TestVideoIdExtraction::test_extract_video_id_standard_url -v  # Single test

# Linting & Formatting
make lint                   # Run ruff linter + format check
uv run ruff check src/ --fix   # Auto-fix lint issues
uv run ruff format src/     # Format code

# Type Checking
make typecheck              # Run mypy

# All Checks
uv run pre-commit run --all-files

# Documentation
uv run --extra docs mkdocs build --strict

Project Structure

src/
  gobbler_cli/      # CLI commands (Typer-based)
  gobbler_core/     # Core converters and providers
  gobbler_relay/    # WebSocket relay for browser extension
  gobbler_queue/    # SQLite-backed background job queue and worker
skills/             # AI agent skill definitions
tests/unit/         # Unit tests
tests/integration/  # Integration tests
tests/e2e/          # End-to-end tests

Code Style

  • Python 3.11+ required
  • Line length: 100 characters max
  • Type hints: Strict mode - all public functions must have annotations
  • Docstrings: Google-style, required for public functions
  • Imports: Organized by ruff/isort (stdlib, third-party, first-party, local)

First-party packages: gobbler_core, gobbler_cli, gobbler_relay, gobbler_queue

Type Annotations

# Use modern syntax
async def convert(url: str, provider: Provider | None = None) -> tuple[str, dict]:
    ...

Read the full file on GitHub · 162 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 162 lines · 1,122 tokens per session scan A 62c7b22b0f49

Subscribe to this mod's changes

gobbler AGENTS.md is an instructions file published in the GitHub repository Enablement-Engineering/gobbler (4 stars, last pushed 9d ago), licensed MIT. It adds 1,122 tokens to every session, about $0.0056 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.